Flat panel display characterization: a perceptual approach

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(1)Flat Panel Display Characterization A Perceptual Approach. Kees Teunissen.

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(3) Flat Panel Display Characterization A Perceptual Approach. Proefschrift. ter verkrijging van de graad van doctor aan de Technische Universiteit Delft, op gezag van de Rector Magnificus prof. dr. ir. J.T. Fokkema, voorzitter van het College voor Promoties, in het openbaar te verdedigen op vrijdag 30 januari 2009 om 12.30 uur door Cornelis TEUNISSEN elektrotechnisch ingenieur HTS Dordrecht geboren te Dordrecht.

(4) Dit proefschrift is goedgekeurd door de promotoren: Prof.dr. I. Heynderickx Prof.dr. H. de Ridder Samenstelling promotiecommissie: Rector Magnificus, Prof.dr. I. Heynderickx, Prof.dr. H. de Ridder, Prof.dr. C.M. Jonker, Prof.dr. X. Li, Prof.dr. N. Fruehauf, Prof.dr.ir. G. de Haan, Prof.dr. A.G. Kohlrausch, Prof.ir. K.H.J. Robers,. Voorzitter Technische Universiteit Delft, promotor Technische Universiteit Delft, promotor Technische Universiteit Delft Southeast University, Nanjing, P.R. China University of Stuttgart, Germany Technische Universiteit Eindhoven Technische Universiteit Eindhoven Technische Universiteit Delft, reservelid. The work described in this thesis has been carried out as part of the Research and Development Program within the Business Unit Television of Philips Consumer Lifestyle.. Printed by: Eindhoven University of Technology Cover design: Kees Teunissen and Henny Herps Kees Teunissen Flat panel display characterization: A perceptual approach. Doctoral Dissertation, Delft University of Technology, The Netherlands, 2009. ISBN: 978-90-74445-86-3 Keywords: display characterization, human visual perception, viewing angle, motion artifacts, large-area flicker. Copyright © 2009 by Kees Teunissen All rights are reserved. No parts of this publication may be reproduced, stored in a retrieval system, or transmitted in any form by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission from the copyright owner..

(5) Aan Marion, Joris Sebastiaan en Dirk-Jan En aan mijn ouders en schoonouders. “Door meten tot weten” Nobelprijswinnaar Heike Kamerlingh Onnes, tijdens zijn inaugurele rede in 1882.

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(7) Contents Voorwoord ........................................................................................ 11 Chapter 1 Introduction .................................................................... 13 1.1 1.2 1.3 1.4. History of TeleVision.............................................................................. 13 Display trends ......................................................................................... 16 Display specification............................................................................... 19 Display characterization.......................................................................... 21 1.4.1 Image quality evaluation .................................................................. 22 1.4.2 Image quality description................................................................. 24 1.5 Research framework................................................................................ 26 1.6 Research questions and outline of this thesis .......................................... 27 1.7 References............................................................................................... 29. Chapter 2 A perceptually based metric to characterize the viewing-angle range of matrix displays ........................ 35 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 2.11. Abstract ................................................................................................... 35 Introduction............................................................................................. 35 Experimental set-up ................................................................................ 37 Perceptual evaluation results................................................................... 40 Statistical Analysis .................................................................................. 42 Towards a new metric ............................................................................. 48 Discussion ............................................................................................... 54 Conclusions............................................................................................. 55 Acknowledgments................................................................................... 56 References............................................................................................... 56 Appendix................................................................................................. 58. Chapter 3 A new characterization method to define the viewing-angle range of matrix displays ........................ 59 3.1 3.2 3.3. Abstract ................................................................................................... 59 Introduction............................................................................................. 59 Experimental design................................................................................ 62 3.3.1 General experimental set-up ............................................................ 62.

(8) 3.3.2 Experiment 1: Comparison of two LCDs ......................................... 64 3.3.3 Experiment 2: Comparison of LCDA with a PDP............................ 67 3.4 Experimental results ................................................................................ 68 3.4.1 Result experiment 1: Comparison of two LCDs............................... 68 3.4.2 Result experiment 2: Comparison of LCDA with a PDP ................. 72 3.4.3 Summary of the experimental results ............................................... 73 3.5 Discussion ............................................................................................... 74 3.6 Conclusions ............................................................................................. 75 3.7 References ............................................................................................... 76. Chapter 4 Flicker visibility in scanning-backlight displays ..........79 4.1 4.2 4.3 4.4. Abstract ................................................................................................... 79 Introduction ............................................................................................. 79 Properties of the scanning-backlight system ........................................... 81 Effect of scanning mode.......................................................................... 82 4.4.1 Experimental set-up.......................................................................... 82 4.4.2 Temporal light distribution and model for predicting flicker visibility............................................................................................ 83 4.4.3 Results and discussion...................................................................... 86 4.5 Effect of motion in the image content ..................................................... 88 4.5.1 Experimental set-up.......................................................................... 88 4.5.2 Temporal light distribution of the panel ........................................... 89 4.5.3 Results and discussion...................................................................... 90 4.6 Conclusions ............................................................................................. 92 4.7 Acknowledgements ................................................................................. 92 4.8 References ............................................................................................... 93. Chapter 5 Method for predicting motion artifacts in matrix displays.............................................................................95 5.1 5.2 5.3 5.4. Abstract ................................................................................................... 95 Introduction ............................................................................................. 95 Measurement system ............................................................................... 98 Motion artifacts ..................................................................................... 100 5.4.1 Simulating LCD motion blur.......................................................... 100 5.4.2 Simulating PDP dynamic false contours ........................................ 102 5.5 Perceptual validation ............................................................................. 104 5.5.1 Perceived LCD motion blur ........................................................... 104 5.5.2 Perceived PDP dynamic false contours .......................................... 107 5.6 Discussion ............................................................................................. 109 5.7 Conclusions ........................................................................................... 110 5.8 References ............................................................................................. 111.

(9) Chapter 6 Modeling motion-induced color artifacts from the temporal step response................................................. 113 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9. Abstract ................................................................................................. 113 Introduction........................................................................................... 113 Motion-induced chromatic aberration ................................................... 115 Modeling chromatic aberration ............................................................. 117 Perception experiment........................................................................... 119 Discussion ............................................................................................. 123 Conclusions........................................................................................... 124 Acknowledgements ............................................................................... 125 References............................................................................................. 125. Chapter 7 Epilogue......................................................................... 127 7.1 7.2. Research framework.............................................................................. 127 Conclusions........................................................................................... 128 7.2.1 Viewing angle characterization...................................................... 128 7.2.2 Large area flicker prediction .......................................................... 129 7.2.3 Motion artifact characterization ..................................................... 130 7.3 Discussion ............................................................................................. 131 7.4 Recommendations for further research ................................................. 132 7.5 References............................................................................................. 133. Samenvatting ................................................................................... 135 Summary. ...................................................................................... 141. Curriculum Vitae ............................................................................ 145 Publications...................................................................................... 146.

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(11) Voorwoord De motivatie voor het starten van mijn promotieonderzoek op het gebied van psychofysische beeldkarakterisering wil ik graag kort toelichten. Ik ben mijn carrière begonnen op het instituut voor perceptieonderzoek (IPO) in de groep “zien” en heb daar, naast een gedegen kennis op het gebied van beeldkwaliteitsonderzoek, veel proefschriften, van anderen(!), aan overgehouden. Na mijn overstap naar een productdivisie bij Philips was ik een aantal jaren betrokken bij de productontwikkeling van Plasmatelevisies, waarbij karakterisering van elektro-optische eigenschappen een van mijn verantwoordelijkheden was. Op een gegeven moment ben ik gevraagd om onderzoeksprojecten bij een Chinese Universiteit aan te sturen. De betreffende vakgroep was toentertijd werkzaam in de displayfysica, maar voor Philips Consumer Lifestyle was onderzoek naar beeldschermapplicaties relevanter. Platte beeldschermen genereren hun licht op een andere manier dan de conventionele kathodestraalbuis waardoor het beeld er anders uit kan zien. Het kunnen voorspellen van het waargenomen beeld uit meetbare beeldschermeigenschappen helpt ontwerpers en tv-fabrikanten, zoals Philips, hun producten te verbeteren, zonder ingewikkelde perceptieexperimenten uit te voeren. Aangezien ik zowel in de perceptie alsook in de beeldkarakterisering werkzaam ben geweest was het een leuke uitdaging om dit type onderzoek bij die universiteit op te starten, vorm te geven, en inhoudelijk te begeleiden. Een collega bij Philips Research, hoogleraar in Delft, en ook betrokken bij de samenwerking met de Chinese universiteit, reageerde enthousiast op mijn idee om op dit onderwerp te promoveren, en wilde graag als mijn promotor optreden. Gesteund door mijn fantastische vrouw en kinderen, en nadat het Philips management mijn idee ook positief had ontvangen ben ik vol goede moed in januari 2006 begonnen. Krap drie jaar later is mijn proefschrift af. Ik heb dit kunnen realiseren door een uitstekende medewerking van een aantal mensen. Als eerste wil ik mijn promotor, prof.dr. Ingrid Heynderickx, hartelijk bedanken voor haar in mij gestelde vertrouwen, haar snelle, kundige en accurate terugkoppeling en opbouwende kritiek op mijn artikelen. Ik had mij absoluut geen betere mentor kunnen voorstellen! Daarnaast wil ik mijn medepromotor, prof.dr. Huib de Ridder, hartelijk bedanken voor het op een vakkundige en enthousiaste manier uitzetten van de grote lijnen waarmee de onderwerpen in mijn proefschrift in een logisch verband zijn gezet. Ik ken Huib van mijn IPO-tijd en was zeer vereerd dat hij mijn uitnodiging accepteerde om medepromotor te zijn. De leden van mijn promotiecommissie wil ik bedanken voor hun positieve reactie op de uitnodiging om in mijn promotiecommissie deel te nemen, en daarna mijn manuscript aan een kritische blik te onderwerpen. Jullie 11.

(12) waardevolle suggesties hebben mij geholpen om mijn proefschrift verder te verbeteren. Ik wil mijn paranimfen graag bedanken voor het accepteren van hun rol tijdens de promotieplechtigheid. Prof.dr. Jean-Bernard Martens is sinds vele jaren een zeer gewaardeerde vriend en tennispartner. Dr. Ineke van Overveld is ook al lang een goede vriendin en, bij PiCTionary, een eersteklas tekenares. Natuurlijk wil ik ook het management van Philips Consumer Lifestyle bedanken, met name dr. Kees van der Klauw, Paul Hieltjes, Ton Biemans en Vincent Rikkink. Door hun steun heb ik de gelegenheid gekregen om gedurende een lange periode nauw samen te werken met de Chinese universiteit en de resultaten van ons onderzoek te publiceren. Mijn “Advanced Technology” collega’s bij Philips Consumer Lifestyle wil ik bedanken voor de fijne samenwerking in een goede werksfeer. Vooral de open vorm van communicatie heb ik altijd als zeer plezierig ervaren. I’m also grateful to the team of the Dong Fei Research and Development Center of the Southeast University in Nanjing. In particular, I’d like to thank prof.dr. Xiaohua Li, prof.dr. Yan Tu, prof.dr. Xuefei Zhong, and the PhD students Yuning Zhang, Wen Song, Shaoling Qin, and Lily Wang for their contribution to the work described in this doctoral thesis. Mijn meeste dank gaat echter uit naar mijn vrouw Marion en mijn zoons Joris en Dirk-Jan. Marion, doordat jij de zaken thuis op een uitstekende manier draaiende hebt gehouden, gaf je mij de ruimte om vele avonden en in het weekend aan mijn proefschrift te werken. Daarnaast heb jij mij onvoorwaardelijk gesteund en gemotiveerd, verschillende versies van mijn teksten kritisch bekeken, en mij gevraagd en ongevraagd (maar altijd zeer gewenst) van advies voorzien. Verder mag ik mij gelukkig prijzen met Joris en Dirk-Jan, die goed met elkaar op kunnen schieten en op school prima presteren (inmiddels is “pluskukelen” aan mijn vocabulaire toegevoegd). Gelukkig hebben we de afgelopen jaren ook veel samen kunnen sporten en fantastische vakanties gehad zodat we ondanks de drukte toch een goede familieband hebben behouden. Met de bijdrage van deze mensen is het gelukt om in een prettige sfeer een mooi stuk werk af te leveren, waar ik trots op ben!. HARTELIJK DANK DAARVOOR! Kees Teunissen December 2008 Eindhoven 12.

(13) Chapter 1 − Introduction. Chapter 1. 1.1. Introduction. History of TeleVision. The word “television” is a combination of the Greek word tele, far, and the Latin word visio, sight. Before the nineteenth century, paintings provided a way of capturing a distant scene and show this, often hanging flat on the wall, at another place. Paintings, however, are an artist’s impression of the reality at some point in time. From the onset, the idea of a television system was to capture a dynamic scene at one place and realistically and instantaneously reproduce that scene at another place. Some important milestones to realize this are presented hereafter in a chronological order. It took centuries of advances in chemistry and optics, including the invention of the camera obscura 1 , to enable making permanent photographs. In 1826, the French scientist Joseph Nicéphore Niépce produced such a photograph, which still exists, with a technique called heliography2. He exposed a bitumen-coated copper plate in a camera obscura for several hours in bright sunlight. Thirteen years later, in 1839, the French painter and chemist LouisJacques-Mandé Daguerre photographed, also using a camera obscura, an outdoor scene in Paris with his invented daguerreotype process, using silver instead of bitumen on a copper plate. A much shorter, but still relatively long exposure time (several minutes) prevented moving objects like pedestrians and carriages from appearing in the photo. Subsequent improvements in processes and materials allowed for nearly instantaneous photography (Mees, 1961; Frizot, 1998). Instantaneous photography enabled the English photographer Eadweard Muybridge to shoot his 1878 photo series of a galloping horse with twelve cameras, each outfitted with a trip wire. This is one of the first links to the earliest beginnings of cinematography. The next step to enable live reproduction of dynamic scenes, an essential feature for television applications, required the elimination of the recording medium. Instead of the photographic effect, this could be accomplished by capturing a scene through a photoelectric effect. In the late nineteenth century (1873), one of the first steps to the electric capturing of an image was made by Willoughby Smith and Joseph May, through the discovery of the photo-resistive 1 2. http://en.wikipedia.org/wiki/Camera_obscura http://en.wikipedia.org/wiki/Nicéphore_Niépce 13.

(14) Chapter 1 − Introduction property of selenium (Clark, 1873). Some years later, in 1887, Heinrich Rudolf Hertz observed the photoelectric effect [Hertz, 1887]. These discoveries led to the invention of photoelectric cells which, when arranged in a matrix, could capture an image by converting the electromagnetic waves, in the visible wavelength region, falling onto the cells into electrical signals. A major challenge was finding a way to transmit the electrical information captured by all the photoelectric cells. A solution was provided by Paul Gottlieb Nipkow, who proposed and patented (German Patent #30105, granted in 1885) the world’s first electromechanical television system in 1884, known as the Nipkow disk. The essence of his invention was that an image is scanned point-by-point in a time-sequential order, and transmitted over a single wire. Although this was really a breakthrough, still a lot of development was necessary to generate an acceptable picture at the receiving side. One of the other breakthroughs was the invention of the cathode-ray tube (CRT) oscilloscope, by Karl Ferdinand Braun in 1897. This is the forerunner of today’s CRT-based televisions. The next breakthrough took until January 1926, when John Logie Baird gave a first demo of a television picture with his “televisor”, an electromechanical television system, with mechanical picture scanning based on the Nipkow disk. This system was abandoned in the late 1930s because of its limitations in spatial resolution and brightness (resulting in a coarse and dim image), and a high noise and flicker level (which was visible as a random dot pattern superimposed on the flickering image). The next step, after the electromechanical television, was to develop an all-electronic television system. Philo T. Farnsworth was one of the pioneers with his invention of an imaging tube, the Image Dissector, of which a patent was filed on Jan 7, 1927 (US patent #1,773,980). Although it worked pretty well, its photoelectric sensitivity was limited, and hence other systems, such as the iconoscope (Zworykin, 1934), were introduced for television purposes. This camera was based on a cathode-ray pickup tube that was described in French and British patents, filed in 1928, by Hungarian inventor Kálmán Tihanyi. This electronic television system enabled better picture quality than the electromechanical Nipkow-based systems, due to a better photoelectric sensitivity. Kell and his colleagues at RCA described an experimental television system that used the iconoscope as the pick-up element and a kinescope as the reproducing element (Kell, Bedford, and Trainer, 1934). This experimental television system was a great step forward in enabling live and realistically reproducing distance scenes. Although public television broadcasts, with more than 400 TV-lines, started in mid to late 1930s, the national television system committee (NTSC) issued a technical standard for the transmission of black-and-white television signals with 525 lines of picture 14.

(15) Chapter 1 − Introduction information in 1941 3 . In that same year, commercial licenses for television broadcast were issued to NBC (national broadcasting company) and CBS (Colombia broadcasting system) owned stations in New York. World War-II halted most transmissions, but they were resumed in the period hereafter. In 1953, a compatible color version of the NTSC standard was approved by the Federal Communications Committee (Butler, 2006). From this moment in time, all elements of the television chain were available to capture a dynamic scene at one place and reproduce this scene, instantaneously, on color television displays in the people’s homes. After enabling television at home, developments continued to improve the quality of the reproduced scenes. Obviously, all components of the television chain, depicted in figure 1.1, contribute to the quality of the reproduced image. This thesis focuses on characterizing the image reproduction part, i.e., the display, and its relation with human visual perception.. scene. perception. capture. reproduction. transmission. reception & distribution. Figure 1.1 − The television chain, with from top-left to bottom-right: the scene to be captured, the camera to record the scene, transmission of the camera signal, reception of the transmitted camera signal, the television-set to reproduce the scene, and the viewer who perceives the scene that was captured from a distance.. 3. http://www.ntsc-tv.com/ntsc-main-01.htm 15.

(16) Chapter 1 − Introduction. 1.2. Display trends. Television is a widely used telecommunication system for the transmission, reception, and reproduction of pictures and sound over a distance. The term “television” is also used to refer specifically to the receiving appliance, i.e., the television set (TV). The television set is not just used as a window to the world, but has become a source of entertainment, infotainment, and news. The display, i.e., the component that converts electrical video signals into electromagnetic radiation in the visible wavelength region, is generally the most expensive part of the TV. Starting from 1936 for black-and-white TV and from 1954 for color TV, the CRT dominated the display industry. There have been many improvements over time in various components of the CRT, e.g. in the deflection yoke (Hattori and Song, 2007), the cathode (Yamamoto, 2006), the electron gun (Shirai, 2005), and the phosphors (Yamamoto, 2007). Although the tube depth has been reduced significantly for successive generations CRTs (Meijer, van der Heijden, 2007), the display industry realized that the major disadvantage of a CRT maintains its physical dimension, i.e., its volume, and weight. The industry envisioned a display hanging flat on the wall, like a painting, but this was not possible with the CRT technology. Therefore, the display industry started to develop technologies that enabled wall-hanging displays. For television applications, there are currently two wellestablished flat-display technologies: plasma-display panels (PDPs) and liquid-crystal displays (LCDs). The monochrome alternatingcurrent (AC) type PDP was invented in 1964 at the University of Illinois (Blitzer and Slottow, 1966). At the end of the 1980s, these PDPs were produced for laptop computers, but due to the inability to realize color displays, most PDP manufacturers closed their facilities for monochrome PDPs in 1990 (Shinoda, 2004). The development of color PDPs started in 1967 (DeJule and Chodil, 1975); first a twoelectrode and later, in 1984, a three-electrode PDP was developed (Shinoda and Niinuma, 1984; Dick, 1985). Large size PDPs (around 42-inch in diagonal) were successfully introduced for television applications around the year 2000 (Shinoda, 2004) and they are still used for TV-applications. At present, Plasma-TVs with a diagonal screen size up to 103 inch are commercially available and even prototypes with a 150-inch diagonal have been demonstrated (Ashida, Murakoso, Wada, Okawa, Yamamoto, Ando, et al., 2008). Heilmeier, of RCA Laboratories, discovered the liquid crystal guest-host mode and dynamic-scattering mode in the same year the AC-PDP was invented (1964) and envisioned that a wall-sized flatpanel color LCD-TV was just around the corner (Kawamoto, 2002). It took about 25-years of research, including the discovery of the 16.

(17) Chapter 1 − Introduction twisted-nematic liquid crystal mode (Schadt and Helfrich, 1971; Fergason, Taylor, and Harsch, 1970) and the concept of active matrix driving (Lechner, Marlow, Nester, and Tults, 1971), before Sharp demonstrated in 1988 a 14-inch color LCD unit (Nagayasu, Oketani, Hirobe, Kato, Mizushima, Take, et al., 1988). This panel had a native resolution of 642 (horizontal) × 480 (vertical) pixels and a contrast ratio (defined as the maximum luminance in the white state divided by the minimum luminance in the black state) of more than 100:1, which was at that time a major achievement. A press release on an actual wall-hanging television product was made by the same company in 1991 (Sharp, 1991). Subsequent improvements in the liquid crystal mode were necessary to enable large screen televisions. To improve the poor viewing angle performance of TN-mode LCDs (Li, He, Ding, 1997), alternative liquid crystal modes were developed, such as: in-plane switching (IPS; Hitachi, 1996), multi-domain vertical alignment (MVA; Koike and Okamoto, 1999), and patterned vertical alignment (PVA; Souk and Kim, 2000). Despite all efforts to improve the image quality of large screen televisions, the main reason for consumers to buy one was its slim form factor. The image quality of CRT-based TVs was in 2005 still superior to that of flat-screen TVs in aspects like motion portrayal, rendering of dark details, and natural color rendering (Heynderickx, and Langendijk, 2005). With the introduction of high-dynamic-range displays (McCann, 2007) the black level of the LCDs is improved, where LC voltage overdriving (McCartney, 2003) and fast response LCDs (Shin, Oh, Kim, Park, and Berkeley, 2008) were introduced, preferably in combination with a reduced hold-time (Sluyterman, 2005), to improve the motion portrayal. These developments, together with huge investments in large scale factories, resulted in a competitive price (with the CRT as a reference) for these displays. They are now widely accepted in consumer products (notebook PCs, monitors as well as TVs) and, as a result, the CRT share in television shipments is now rapidly decreasing (figure 1.2). As a result of these technological developments, more and more flat screen televisions appeared on the market and hence, consumers became more critical towards differences in image quality between these televisions during their buying decision. Therefore, although the LCD technology has progressed with incremental and revolutionary improvements, still significant research efforts are ongoing to even further improve the display performance. Some examples of ongoing LCD-related research topics, presented during the SID’08 Display week in Los Angeles, include but are not limited to: fast liquid crystal response time, contrast enhancement, high resolution, viewing angle improvements, motion blur reduction, backlight modulation, and color-gamut extension. Obviously, these research efforts will lead to a better product specification on paper. 17.

(18) Chapter 1 − Introduction However, are all efforts to improve the display performance also perceived and appreciated by the consumers? Teunissen and van der Klauw (2007) substantiated that consumer appreciation for a television is not necessarily linked to the defined set of technological display parameters (like response time, contrast ratio, maximum luminance, number of pixels) and performance indicators (for instance, motion picture response time [Igarashi, Yamamoto, Tanaka, Someya, Nakakura, Yamakawa, et al., 2004], color gamut size, and viewing angle based on a contrast ratio > 10:1). Linking human visual perception to the physical display characteristics helps to predict when display improvements are perceivable. This requires knowledge about the human visual system, display physics, and visual assessment techniques. Before discussing display characterization and visual assessment techniques, we will briefly discuss applicability of knowledge about the human visual system to define detail-related image characteristics of a display during the early days of television.. TV shipments by display type 100% PDP. 80%. LCD. 60%. CRT. 40% 20% 0% 2006 2007 2008 2009 2010 2011. Figure 1.2 − Predictions of the relative share in TV shipments for several display technology (based on data from Displaysearch report, Q1-2008).. 18.

(19) Chapter 1 − Introduction. 1.3. Display specification. In the early days of television, engineers had to define the system requirements to develop the individual components. Practical system implementations were checked against the characteristics of the human visual system. In 1862, the Dutch ophthalmologist Herman Snellen developed a chart to test the human visual acuity. The visual acuity is a quantitative measure to test the ability of the human visual system to correctly detect specially shaped black characters (optotypes) on a white background at a standardized viewing distance and specified illumination level, as the size of the characters is varied. Snellen defined “standard vision” or “normal vision” as the ability to recognize optotypes that subtended 5 minutes of arc. Due to the nature of his optotypes, i.e., the letter height and width are five times the line thickness and letter gap, this corresponds to an ability to discriminate a spatial pattern separated by a visual angle of 1 minute of arc. One could argue that the definition of normal vision is also applicable to determine the required number of TV scanning-lines per viewing distance, even though both pattern and illumination condition are different from the printed optotypes. In the early 1930s, the inability to produce television images of sufficient size, detail, and light output, prevented the use of real television systems in practical experiments. Engstrom (1933), for instance, first used charts with patterns that may have been obtained with actual television scanning systems. The results of a perception experiment, with three participants, revealed that, depending on the pattern, between 0.5 to 2 minutes of arc separation between the centers of the scanning lines was required to resolve both lines. However, the required separation between the scanning lines (on average 1 minute of arc) was assumed not representative for real television images, because charts were used. To draw conclusions on the desired number of scanning lines for motion pictures, Engstrom conducted a second experiment with image sequences of different resolution (number of scanning lines). For these sequences a separation of, on average, 2 minutes of arc was sufficient to just resolve the picture details 4 . This result was (and still is) useful to determine the optimum number of scanning lines for a particular viewing distance. For example, a 28” display with an aspect ratio of 4 (width) by 3 (height) in standard definition (PAL) resolution (720 pixels per line x 576 lines) comprises about 34 lines per inch. According to figure 1.3, the optimum viewing distance for an observer with normal vision (1 minute of arc) is about 2.5 meter. This distance is equivalent to 6 times the screen height, i.e., 43 cm for the 28-inch TV, for which the 4. For a display luminance of 20 cd/m2. 19.

(20) Chapter 1 − Introduction PAL system was designed. When the viewing distance is larger than the optimum distance, the display is over-specified, i.e., the display can show more details than the average eye can resolve. As a result, the specification of a display should be optimized for its application. A computer monitor is commonly viewed from a short distance (e.g. 60 centimeter), independent of the display size, and needs more scanning lines per screen height to make the individual lines just not visible (see figure 1.3). It does not make sense to use the same criteria for different application areas. visual acuity: 0.5' visual acuity: 1' visual acuity: 2' 17" monitor: 1024-lines 28" TV: 576-lines. scanning lines per inch. 200 160 120 80 40 0 0. 50. 100. 150. 200. 250. 300. 350. 400. 450. 500. Viewing distance (cm). Figure 1.3 − Theoretical approach to determine the number of scanning lines per inch needed at a given viewing distance considering three levels of visual acuity: 0.5 minutes of arc, 1 minute of arc, and 2 minutes of arc. Another display property addressed by Engstrom (1935) is large area flicker. System designers had to balance the amount of spatial detail to be transmitted versus the temporal resolution (or refresh rate), i.e., the frequency with which the image is updated. Accurate reproduction of an image demands transmitting a high amount of spatial information, but this also requires a long transmission time. From cinematographic film it was known that 24 pictures per second suffice to capture movements, but at the reproduction side, the rate of showing the pictures should be doubled to avoid serious display flicker. In his study, Engstrom found that the flicker visibility depends not only on the refresh rate, but also on the display luminance and the effective illumination time (duty cycle of the light generation). From a display characterization point of view, Farrell et al., (1987) published an analytical model to calculate the critical fusion frequency (CFF), i.e., the frequency for 20.

(21) Chapter 1 − Introduction which an observer starts to notice flicker. This tool is helpful to predict from the time-varying luminance, produced by the display, whether an observer detects flicker or not. The model is based on the groundbreaking visual perception work conducted by scientists, like de Lange (1958a,b, 1961), Kelly (1961), and Roufs (1972a,b, 1973). Thus, both system specification and system characterization can benefit from knowledge about the human visual system.. 1.4. Display characterization. Displays can be characterized subjectively, with human observers, physically or objectively, with instruments, or psychophysically, relating instrument values to human visual perception (see figure 1.4).. Display. assess. measure. Observer. Instrument relate. Figure 1.4 − Display characterization alternatives. Our focus is on psychophysical display characterization, because, typically, the physical measurements are obtained and kept separately from the subjective judgments (the psychological component). Although psychophysical measurement and evaluation is well described in the literature (for instance de Ridder, 1998; Martens, 2003), we provide some background on subjective assessment techniques in the next section, assuming that knowledge in this field of research is not fully deployed in the engineering society.. 21.

(22) Chapter 1 − Introduction. 1.4.1 Image quality evaluation Advances in the individual components of the television chain (figure 1.1) resulted, for instance, in a higher spatial density of the captured scenes. Consequently, more video data needed to be transmitted and reproduced on the display. Various image compression techniques were developed to reduce the number of data-bits to be transmitted. In the process of image compression, it is evident that image details are removed and visual disturbances can become visible after decompression. Because no objective models were available to quantify the visibility of the disturbances, various test laboratories were involved to assess the subjective quality of the impaired images, resulting from those algorithms. The adoption of a single standardized assessment method was of great importance to exchange and compare results between these laboratories. Ideally, the outcome of the subjective evaluation experiments should neither be biased, nor influenced by experimental methodology, experimental protocol, experimental settings, or environmental influences. In 1974 the International Radio Consultative Committee (CCIR) published its first Recommendation 500 (CCIR, 1974) “Method for the subjective assessment of the quality of television pictures”, now known as ITU-R BT.500 (ITU, 2002). This first recommendation was based on the work of Prosser, Allnatt, and Lewis (1964), who proposed a general-purpose quality-grading method. In this CCIR recommendation three grading scales were defined to assess visual quality (see table 1.1): the five-point Quality scale, the five-point Impairment scale, and the 7-point Comparison scale. Table 1.1 − CCIR recommended grading scales (CCIR, 1974). Five-point scale. Comparison scale. Quality. Impairment. +3. Much better. 5 Excellent. 5 Imperceptible. +2. Better. 4 Good. 4 Perceptible, but not annoying. +1. Slightly better. 0. The same. 3 Fair. 3 Slightly annoying. -1. Slightly worse. 2 Poor. 2 Annoying. -2. Worse. 1 Bad. 1 Very annoying. -3. Much worse. 22.

(23) Chapter 1 − Introduction Next to the grading scales, also the viewing conditions were standardized. For most assessments a dark surround was indicated as most critical for showing artifacts, but a dim surround was considered to better represent living room conditions. The viewing distance was defined such that the angular pixel size was about 1 minute of arc, which for a PAL display with an aspect ratio of 4 over 3 and an active display area of 576 lines by 720 pixels per line led to a viewing distance of 6 times the screen height (described in section 1.3). To enable a statistically relevant analysis the minimum number of observers to participate in an experiment was also specified. The results for expert viewers, those who have recent extensive experience in observing picture impairments occurring in the test, are known to be different from those of non-expert viewers (Prosser, et al., 1964; confirmed by Westerink, 1989, and Heynderickx and Bech, 2002). Therefore, expert viewers were prescribed to be treated separately from non-expert viewers. Because observers are incapable of ignoring their previous responses, it was recommended that the pictures and impairments were presented in a pseudo-random presentation order to minimize sequential effects. A final item for consideration was the usage of the judgment scale. The doublestimulus method with a continuous quality scale was proposed, which was divided in 5 intervals of equal length. For guidance the same adjectives used for the 5-grade quality scale were positioned along the graphical scale. However, a study conducted by Teunissen (1996) revealed that the translated quality terms, recommended by the CCIR, did not divide the quality scale into intervals of equidistant sensations, and so turned the judgment scale in an ordinal scale rather than an interval scale. Nevertheless, the double stimulus method with a continuous quality scale was used successfully for the evaluation of different coding algorithms. The results demonstrated a remarkable resemblance in obtained mean quality scores carried out at 5 different test sites (Westerink, 1991). The main purpose of the ITU-R BT.500 recommendation is providing a standardized methodology to assess quality differences between imaging systems, rather than exploring the underlying factors describing the differences in image quality. The need to understand image quality is nicely expressed by Biberman (1973): “It is a truism that a good picture is better than a bad picture, but is has not been abundantly clear, especially to designers of most electro-optical imaging systems, what criteria must be used to decide if a picture is good or bad”. The perceptual image quality judgment must be decomposed into the underlying quality dimensions to obtain a better understanding how to systematically optimize image quality.. 23.

(24) Chapter 1 − Introduction. 1.4.2 Image quality description In their paper, Roufs and Bouma (1980) advocate the use of a systematic approach in quantitative modeling, to promote generalization with respect to the prediction and evaluation of the perception of images. They already recognized that ad hoc research for engineering problems, in which perception is involved, could not lead to generally applicable results. However, the considerable amount of initial effort, without the guarantee of timely arriving at a satisfactory model to predict image quality, withheld many companies in the display and television industry to adopt this systematic approach. Therefore, this topic was mainly addressed by universities and other academic institutions. One of the developed methodologies to systematically assess image quality of displays is the RaPID Perceptual Image Description Method (Bech, Hamberg, Nijenhuis, Teunissen, Looren de Jong, Houben and Pramanik, 1996) which aimed at a rapid and perceptually meaningful description and quantification of the primary factors of image quality. It is built on a model developed by Nijenhuis (1993), in which the perceptual factors that contribute to image quality differences are described and quantified. The model assumes that a display system can be characterized with a set of physical parameters, such as spatial and temporal resolution, luminance, and color coordinates. These physical parameters relate to perceptual attributes, i.e., sensed visual information. Examples of attributes are sharpness, large area flicker, brightness, darkness, and colorfulness. During an experiment, these attributes are assessed on their perceptual (or sensory) strength, and via complex mental processing these sensory strengths lead to an impairment score for each of the relevant attributes. Subsequently, accumulation of small image coding impairments can, for instance, be described by a Minkowski-metric with an exponent of about two (de Ridder, 1992). Finally, the overall impression of image impairments is expressed in just one image quality judgment score. There are three parallel assessment paths defined in the RaPID approach: (1) the physical image of the display is objectively characterized with physical measurements, (2) it is perceptually characterized with expert viewers, who determine the perceptual strength of the attributes, and (3) the perceived image quality is evaluated with a group of selected consumers (non-experts in the field of perception or video processing). This approach is depicted in figure 1.5. The image quality circle (Engeldrum, 1989, 1999, 2004), depicted in figure 1.6, is another representation of the same approach to systematically assess image quality. The main idea of both approaches is to separate evaluation of the individual perceptual attributes from the evaluation of the overall image quality. 24.

(25) Chapter 1 − Introduction In the image quality circle approach, display engineers characterize the physical image, and mainly vision scientists and psychologists characterize the relation between the perceptual attributes and image quality. The field of psychophysics, addressed in this thesis, provides the link between both research fields and aims at perceptually relevant display specification.. Physical Space. Expert Viewers team. Consumer Research. Display Under Test. Physical measurements. Perceptual Attributes. Objective metrics. Image Quality. Quality metrics. Technical parameters. Figure 1.5 − The RaPID approach to evaluate and optimize imaging systems. Figure 1.6 − The image quality circle according to Engeldrum (2004). 25.

(26) Chapter 1 − Introduction. 1.5. Research framework. Television is a well established medium to provide a window to the world. For decades, cathode-ray tubes (CRTs) have dominated the display industry, but their form factor did not allow wall-hanging TVs and their diagonal screen size was limited to about 32-inch. As a result, flat display technologies, such as liquid-crystal displays (LCDs) and plasma-display panels (PDPs) have been introduced and they have changed the display landscape, where LCDs are today the dominant display technology. Although the display performance of flat-display technologies has progressed with incremental and revolutionary steps, still display and television manufacturers invest in research and development to improve their products. The result of their efforts, however, is not always visible for non-experts. Sometimes, special test patterns are required to demonstrate the technological improvements. Next to that, it is often difficult to communicate an advanced technological breakthrough in a terminology that the consumer can understand. For the consumers it is very difficult to compare the product specifications due to the variety of manufacturer-specific terms and the non-standard way of measuring and specifying the technological specification items. Apparently, it is not easy to change this situation. In an industrial, technological, environment it is not always common practice to involve consumers in the definition of specification items. Display engineers use measurement equipment, developed to characterize the electro-optical performance of displays, such as luminance meters, color analyzers, spectroradiometers, and conoscopic instruments. The engineering-based objective models are used to characterize the display performance from the measured values, such as contrast ratio, color-gamut size, and viewing angle (based on the ratio between black and white). A limitation of these objective models is that most instruments do not include properties of the human visual system, and as a consequence, the predictive power for what we actually perceive is typically low. On the other hand, in the field of experimental psychology, methodologies have been developed to evaluate the perceived image, but psychologists are not primarily interested in the underlying technological details. When the knowledge of both worlds (engineers and psychologists) is combined in the development of psychophysical characterization models, useful results are obtained to benchmark and optimize the performance of flat-panel display technologies, without the necessity to involve human observers. Additionally, the provided values are useful to communicate display properties to the (non-technical) endconsumers.. 26.

(27) Chapter 1 − Introduction A framework to systematically optimize the performance of imaging systems consists of a 3-step approach: 1) The physical image as rendered on the imaging system needs to be characterized via measurement or via simulation models. 2) The relevant perceptual attributes of the physical image as perceived by the viewer need to be identified and evaluated separately via subjective assessment or derived from the physical image via human visual perception models. 3) The perceived image quality, an integrated perception over all attributes, needs to be determined via subjective assessment or via a weighted combination of the relevant perceptual attributes. When all three elements of the above mentioned approach are completed, it should be possible to predict the perceived image quality from the technological variables, which is actually the relation where the display industry is eagerly looking for.. 1.6. Research questions and outline of this thesis. Considering the complexity of the image quality framework, and the missing link between physical characterization and perceptual evaluation, the scope of this thesis is confined to establishing psychophysical relations. In other words, this thesis focuses on the question: What are the relevant physical parameters to characterize a matrix display in a perceptually relevant way? In this broad field of research, we have focused on three display characteristics that were relevant at the start of our research: 1. Viewing angle characterization. The metric (CR>10:1) to determine the viewing angle range of LCDs was defined in the 1970s, when the twisted nematic LC mode was commonly used for LCDs. At present, alternative LC-modes are used for television applications and the product specification for all TVs indicates a viewing angle range, approaching 180 degrees. However, one could question if the old metric is still adequate to describe performance differences between displays. This question is addressed in chapters 2 & 3.. 27.

(28) Chapter 1 − Introduction 2. Large area flicker. One of the alternatives to improve the motion performance of LCDs is using a scanning backlight LCD, in which the backlight is modulated (switched on and off) within a frame period. Under specific conditions, backlight modulation may introduce large-are flicker: like for instance with 50-Hz CRTbased televisions. Analytical models to predict flicker visibility for CRT-based displays have been described in literature, but are these models also applicable for scanning backlight-type LCDs? The results of this study are described in chapter 4. 3. LCD motion artifacts. LC voltage overdriving techniques and fast LC modes have been introduced to improve the motion performance of LCDs. However, next to the LC response time, also the sample-andhold effect contributes to the motion performance of LCDs. By nature, LC-cells maintain their addressed state throughout the whole frame period, before a next state is assumed. When human eyes track an object moving across the screen (thus over many LC-cells), the intensity of the LC-cells is smeared over the human retina. A more detailed explanation of this phenomenon will be provided in chapter 5. The question, addressed in this thesis is whether it is possible to predict the perceived edge profile of an object, when the object is moving across the screen? The approach to characterize motion-blur is disclosed in chapters 5 & 6. In chapter 7, the obtained results are shortly reviewed on their contribution to the image quality framework and the conclusions of the work are provided. Also an extension of the image quality model towards characterizing viewing experience is addressed, and some directions for future research are presented.. 28.

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(33) Chapter 1 − Introduction Scale,” SMPTE Journal, Volume 105, Number 3, 144 – 149 (1996). Teunissen, C., and van der Klauw, C.L.M., “Display technology trends perceived from a consumer (electronics) point of view,” (Invited paper) Proceedings of the 14th International Display Workshops, 2271 – 2274 (2007). Westerink, J.H.D.M., “Influences of subject expertise in quality assessment of digitally coded images,” SID International Symposium Digest of Technical Papers, Volume 20, 124 – 127 (1989). Westerink, J.H.D.M., “Perceived Sharpness in static and moving images,” PhD thesis, Technical University Eindhoven, the Netherlands (1991). Yamamoto, H., “History and future of CRT phosphor technologies,” Proceedings of the 14th International Display Workshops, 765 – 768 (2007). Yamamoto, S., “Oxide cathodes for today and tomorrow,” Proceedings of the 13th International Display Workshops, 1037 – 1040 (2006). Zworykin, V.K., “The iconoscope – A modern version of the electric eye,” Proceedings of the Institute of Radio Engineers, Volume 22, Number 1, 16 – 32 (1934).. 33.

(34) Chapter 1 − Introduction. 34.

(35) Chapter 2 − Characterization of viewing-angle range. Chapter 2. 2.1. A perceptually based metric to characterize the viewingangle range of matrix displays5. Abstract. The current specification of a display’s viewing angle as the angle within which the contrast ratio is larger than 10:1 appears not to be predictive for the acceptable viewing-angle range obtained from perception experiments. In our search towards a perceptually relevant specification for the viewing angle, the physical characteristics of the display that are most related to the viewing-angle-dependent image quality were analyzed. This was done for two types of liquid-crystal displays and one plasma TV. The results indicate that a combination of the luminance and chromaticity coordinates of the higher grey levels predicts the degradation in image quality as a function of viewing angle. As a consequence, a new definition of a display’s viewing-angle range is proposed based on these characteristics.. 2.2. Introduction. It is known that most, if not all, display technologies exhibit their own particular artifacts (Heynderickx, and Langendijk, 2005). Liquid-crystal displays (LCDs) are popular, despite issues with motion blur and viewing-angle dependent image quality. Their counterpart, the self-emitting plasma displays (PDPs), perform quite well under oblique viewing angles. Their performance is similar to that of cathode-ray tube (CRT) displays, and claimed to be superior to that of LCDs. The problem of an off-angle performance deviating from the perpendicular view in the case of an LCD originates from changes in polarization and related light leakage in the liquid-crystal cells. Several techniques, such as in-plane switching (IPS), patterned vertical alignment (PVA), and multi-domain vertical alignment (MVA), are proposed to improve the LCD’s off-angle performance. In order to. 5. This chapter has been published in the Journal of the Society for Information Display, Volume 16, Number 1, 27 – 36 (2008): “A perceptually based metric to characterize the viewing-angle range of matrix displays”, C. Teunissen, S. Qin, and I. Heynderickx. 35.

(36) Chapter 2 − Characterization of viewing-angle range quantify these improvements, an appropriate definition for the viewing-angle performance is necessary. For decades, it has been common practice to characterize the viewing angle of LCDs as the range in horizontal, and sometimes vertical, direction within which the contrast ratio (CR) is equal to or larger than 10:1. This might have been a meaningful specification in the past, when LCDs faced the problem of obtaining a maximum CR larger than 100:1. Now that LCDs commonly have a CR for the perpendicular viewing direction, of the order of 1000:1, one can wonder whether the specification of a CR larger than 10:1 under an oblique angle is still relevant or needs to be revised. Some LCD makers already specify the viewing angle range for a CR larger than 50:1 (Yamada, Kimura, and Ishii, 2005), but it is questionable whether this specification delivers a better characterization of the viewing-angle range. One can even doubt whether it is legitimate to specify the viewing-angle range using only the contrast ratio because the image on an LCD viewed under an oblique angle is not only characterized by a reduced luminance range, but also by deviations in color (Okamoto, 2006). Recent attempts to find a perceptually more-relevant measure for the viewing angle are published in the literature. Shimodaira and his colleagues (Ozawa, Shimodaira, and Ohashi, 2004) use an approach in which they first subjectively measure the effect of black level, white level, gamma, and saturation decrement of the primaries on image quality separately. They then develop an overall quality model using a perceptually weighted summation over all image degradation contributions (except for the black level, since its effect on image quality is found to be negligible). Based on this model, they define the viewing angle as the width of the cone for which the overall quality has a score of 1 or more. So, from the physical characteristics of an LCD, the various quality terms in the summation can be derived from graphs in their paper, and from these graphs the overall quality can be calculated. For all of the six LCDs measured, they found that the resulting viewing angle is considerably smaller than the one resulting from the constraint of a CR of 10:1. A disadvantage of this approach, however, is that the viewing angle is not directly related to the physical characteristics, but only via an intermediate step, existing of the quality contributions per physical characteristic. As a consequence, the viewing angle can only be calculated for displays with physical characteristics in the range for which the image-quality contribution is known. Also, other research groups (Suzuki, Takizawa, 2002; Hisatake, Obi, Itoh, Tago, Kawata, and Murayama, 2005; Huang, Huang, Wu, Tsao, Su, Chang, et al., 2005; Yamada, Mitsumori, Miyazaki, and Ishida, 2005) recognized that grey-scale (or gamma tone-response curve) and/or color differences should be included in. 36.

(37) Chapter 2 − Characterization of viewing-angle range a perceptually relevant measure for the viewing angle. They defined metrics expressed in luminance or color differences, and found a good correlation with subjectively measured viewing angles. All the approaches reported thus far have one aspect in common: they only include physical characteristics assumed to be important for the viewing-angle-dependent image quality. Other characteristics are excluded from the beginning. Of course, it makes sense to assume that the perceived viewing angle depends on the black level, white level, gamma, and color differences. But, for example, focusing only on saturation decrements of the primaries might be a limitation that is not justified. Hence, to avoid possible preoccupation, a bottom-up statistical approach is chosen to extract the relevant physical characteristics. Each of the displays used in the perceptual evaluation of the viewing angle is fully characterized by measuring many points along each primary’s response function, including the neutral. All these data are then used in a statistical analysis in order to find which characteristics contribute most to the variation in quality as a function of viewing angle. Because it is anticipated that characterization of the viewing-angle range with a limited number of physical measurements would increase the acceptance of a new metric in the display industry, the full set of physical characteristics is then reduced to a limited set of the most relevant characteristics. With this reduced set of physical parameters, a simple metric that shows a high correlation with the perceived image quality for all displays is defined. This metric is used to propose a new criterion to define the viewing-angle range of matrix displays.. 2.3. Experimental set-up. The objective of the study reported in this paper was to identify the physical properties that define changes in image quality related to changes in the viewing angle for matrix displays in general, and from these physical characteristics derive a new criterion that specifies the viewing-angle range of a display. Considering the differences in technology, two different types of LCD panels (LCDA and LCDB, based on IPS- and MVA-type technologies) and a plasma display panel (PDP) were used for our experiment. The LCDs had a native display resolution of 1280 × 768 pixels, and no intermediate processing was involved between the source material and the display. The PDP, on the other hand, was a television set (TV) with some unknown intermediate processing between the source material and the display, and had a native resolution of 1024 × 768 pixels. The intermediate processing and required format scaling, to fit the display resolution, did not visibly degrade the stimuli. The viewing-angle performance was evaluated for one single display at the time because this set-up reflected the home situation, 37.

(38) Chapter 2 − Characterization of viewing-angle range where consumers watch the TV from different positions. Another reason for this approach was our aim to arrive at a metric that defines the viewing-angle range related to the initial quality of the display in its perpendicular view. During the experiment, each display was separately mounted in a holder, which could rotate horizontally in both right and left directions and vertically up and down (see figure 2.1). Each display, i.e., LCDA, LCDB, or PDP, was evaluated in a separate session with 20 non-expert participants (11 females and 9 males for LCDA; 7 females and 13 males for LCDB and PDP). The age of the participants was within the range of 22-73 and all of them had (corrected to) normal vision (≥1.0 on a Landolt chart) and no color deficiencies (tested with the Ishihara color-vision test charts). Five still images, shown in figure 2.2, were chosen to include a representative mix of image content in the evaluation. For each session, the experimenter turned the holder, at a fixed vertical angle, in horizontal direction with a speed of approximately 1 deg/sec. Meanwhile, the participant was asked to indicate the horizontal position at which a perceptual change in the image was detected with respect to the initial position, hereafter referred to as the visibility threshold. Afterwards, the horizontal angle was further increased until the participant indicated that the perceived quality of the image was deemed unacceptable, which is hereafter referred to as the acceptability threshold. Visibility and acceptability threshold angles were recorded by the experimenter. Additionally, participants were requested to score the perceived image quality at all threshold angles on an 11-points numerical scale, with 0 corresponding to the lowest quality and 10 to the best quality for the display under test. Finally, they were asked to indicate one or more reasons that supported their decision. This procedure was repeated for both a left and right rotation in the horizontal direction, at five different vertical viewing angles (0, ±22.5º and ±45º) for all five images. Ambient illumination influences were minimized by using a low room illumination level of 5 lux, measured at the screen in the direction of the viewer with the display turned off. The distance from the display to the viewers was equal to six times the screen height.. 38.

(39) Chapter 2 − Characterization of viewing-angle range. Figure 2.1 − Photograph of the experimental set-up, with the holder enabling both horizontal (green arrow) and vertical (red arrow) rotation of the display. The height of the chair was adjustable to align the participants’ eyes with the screen center.. Bright. Skin-tone. Grayscale. Colorful. Dark. Figure 2.2 − Image material used in the perception experiment. 39.

(40) Chapter 2 − Characterization of viewing-angle range. 2.4. Perceptual evaluation results. As reported above, the evaluations were performed for a left and right rotation of the display in the horizontal direction separately, per vertical angle and participant. As a consequence, four threshold values (2 × visibility and 2 × acceptability) were determined for each vertical angle. The resulting viewing angles at visibility and acceptability threshold, averaged over the participants, are shown in figure 2.3 (already reported in the literature: Qin, Zhong, Heynderickx, Teunissen, Lian, Xia, et al., 2006; Qin, Zhu, Yin, Xia, Teunissen, and Heynderickx, 2006).. Horizontal threshold (degrees). Horizontal threshold (degrees). 70 60 50 40 30 left visibility left acceptability right acceptability right visibility. 20 10 0 -50. -30. -10. 10. 30. LCDB. 80. LCDA. 80. 50. 70 60 50 40 30 left visibility left acceptability right acce ptability right visibility. 20 10 0 -50. -30. 10. 30. 50. PDP. 80 Horizontal threshold (degrees). -10. Vertical viewing angle (degrees). Vertical viewing angle (degrees). 70 60 50 40 30 left visibility left acceptability right acceptability right visibility. 20 10 0 -50. -30. -10. 10. 30. 50. Vertical viewing angle (degrees). Figure 2.3 − Visible and acceptable horizontal viewing angles as a function of the vertical viewing angle for the three displays used in this investigation. The whiskers in the graphs indicate the 95% confidence interval.. 40.